This internship aims to implement perception systems for autonomous vehicles. According to the literature, analysing the surrounding scene has been treated by the data fusion (evidential theory) and by the neural networks (Deep Learning). The objective is to select an algorithm of both approaches, regarding their performance ("false positive", classification accuracy...) as well as their computational cost before implementing them into the embedded systems of the autonomous vehicles of IRIMAS. Real-field experiments will be realized, and the results will be analysed. From this practical, embedded systems internship will raise research directions regarding the design of an algorithm combining data-based and model-based approaches. The internship is for 6-months duration with regular internship salary. It will take place in the IRIMAS laboratory in Mulhouse, France